The Top 50 Python Courses Online

Python is among the most popular programming languages, thanks to its object-oriented features and versatility. Those interested in programming should learn Python to take advantage of its clean syntax and ability to complete complex tasks. The following online courses are helpful for learning to use Python.

1. Free Python Tutorial – Learn Python 3.6 for Total Beginners

As the name implies, this course is perfect for beginners, offering a basic understanding of Python 3.6 in just a day. It covers all of the basics, including:

  • Understanding and using lists, dictionaries, and tuples
  • Applying control flow or logic to code
  • Implementing functions
  • Converting functions to lambdas
  • Converting loops to list comprehension
  • While and for loops
  • Txt files
  • Formatting strings

The course uses Jupyter Notebook IDE and also includes seven exercises, complete with solutions, for students to practice these new skills.

2. CS101 Learn to Code with Python

This course is perfect for beginners who want to begin using Python to code. A trained university instructor runs the course, which teaches the skills needed for professional coding. It teaches students to code in Python at the university level, including solving programming problems. From there, students learn how to code at a professional level. There are also five projects in the course, complete with tips. Once students complete the projects, they should have the skills to use Python as a professional.

3. AI Programming with Python

AI Programming with Python allows students to hone their skills in Python, Pandas, Matplotlib, NumPy, PyTorch, calculus, and linear algebra, providing the necessary background to create neural networks. The course covers the essentials in each of these categories, so students can begin creating artificial intelligence applications within just three months. This particular course is a strong choice for those who want to learn about not only Python but also AI, as neural networks are its building blocks.

4. Learn Practical Python 3 for Beginners (2018)

The course is ideal for beginners who want to learn Python. It uses Jupyter Notebook and guides students through the tools within it, as well. The course covers:

  • Lists, dictionaries, sets, and tuples
  • Converting lists and dictionaries
  • For loops and while loops
  • The os module, pickle files, and txt files
  • Generators and functional programming
  • Object-Oriented Programming
  • NumPy, Pandas, and Matplotlib
  • Functions and lambda expressions

The course features 11 exercises to help students hone these skills, complete with solutions in multiple formats.

5. Programming for Data Science with Python

This Python online course is ideal for those who want to go into data science or expand their data science knowledge. The course teaches the most important data programming tools, including Python, command line, SQL, and git. An alternative version of the course focuses on R instead of Python, so be sure to choose the right one. The course will introduce Python programming, version control, and SQL. After the course, students should have many of the programming skills commonly used in data science and data analysis roles. This course does not have any prerequisite knowledge, making it good for beginners, as well.

6. Machine Learning with Python: Data Science for Beginners

Students should be familiar with programming before taking this course. It teaches how to complete machine learning programs using Python. At the end of the course, students will have a better idea of what in machine learning, data science, and artificial intelligence involve. Students will also have the skills to use NumPy, Pandas, and Spyder. Other topics include:

  • Introduction to statistics
  • Supervised and unsupervised learning
  • Linear regressions
  • Cross-validation
  • Ensemble modeling
  • XGBoost
  • Hyperparameter

Although having some familiarity with programming will help, motivated beginners will also enjoy it.

7. Natural Language Processing (NLP) with Python and NLTK

This course teaches students practical applications and concepts associated with Natural Language Processing using both Python and NLTK. It includes collecting and then preprocessing text data, model building, data visualization, and NLP applications. Some key Natural Language Processing topics include using the textract library to textract text content, Part of Speech tagging, rare word removal, and stop. The course includes concise theory reviews and graphical explanations to let students visualize the information. It also includes datasets for further practice.

8. Python Full Stack Web Development with Google Cloud Service

This course teaches Python full-stack web development via six hours of on-demand video, four downloadable resources, and an article. The course teaches the skills necessary to make a full-stack web application from scratch. Students should have basic Python knowledge before taking the course. It will build on that base knowledge, showing how to build a social party web app from scratch with the data stored on Mongo DB. The course also covers the various programs and skills needed to create a full-stack web application, including Flask.

9. Run Unit Tests in Python (+Test-Driven Development)

This Python course teaches Test Driven Development (TDD) that makes use of Python. This is an important skill for programmers to learn as a way to ensure quality code. Students should already have a base level of Python knowledge before taking this course. It will teach:

  • The importance of Test Driven Development
  • How to use the PyTest testing library
  • How to use PyTest with common Python development environments
  • Using test doubles
  • Best practices for Test Driven Development

The course also includes examples of programming with Test Driven Development in Python, so students can connect the knowledge with programming and gain practice.

10. Python Web Automation Testing | Python Selenium Webdriver

This course appeals to those looking to learn about Python web automation testing and Selenium, regardless of experience levels. It is specifically designed for beginners. The course features 25 articles and six hours of on-demand video. The course will allow students to complete website testing and automate websites. The course is also regularly updated with additional modules.

11. The Complete Python Course for Machine Learning Engineers

This course focuses on machine learning engineering and explores the Python knowledge needed for that role. It includes all of the information and skills needed to use Python for creating basic machine learning models. The course also features the various Python-related vocabulary needed for that knowledge.

The course includes hands-on labs to provide experience and test skills. For example, students must build a basic version of a deep neural network one line at a time in Python. Students also build a machine learning model in Scikit-Learn. Students should have basic programming understanding to take this course.

12. CCA 175 – Spark and Hadoop Developer – Python (pyspark)

This course prepares students for the CCA 175 Spark and Hadoop Developer certification, including using Python as the programming language to do so. The course includes knowledge as well as exercises to help students prepare and practice before taking the certification test. The demonstrations all use a state-of-the-art big data cluster. Students in the course also get a week of complimentary lab access.

Some of the topics covered include:

  • Apache Sqoop
  • Python fundamentals
  • Core Spark actions and transformations
  • HDFS commands
  • Spark SQL plus data frames
  • Streaming analytics via Flume, Spark Streaming, and Kafka

13. Learn Practical Python 3 for Beginners (2018)

This course is a great introduction to Python, including its practical applications. It includes 11 exercises that also come with full solutions in various formats. Additionally, the course is regularly updated, so the 2018 in the title does not make it out-of-date.

Because this course appeals to beginners, there are no requirements other than having at least 500 MB available on a computer and an internet connection. By the end of the course, students should have a better understanding of:

  • While and for loops
  • Lists, sets, dictionaries, and tuples
  • Converting dictionaries, sets, and lists for comprehension
  • Using the os module, pickle files, and txt files
  • Object-Oriented Programming
  • Manipulating arrays with numpy
  • Creating interactive graphs using matplotlib
  • Using pandas to manipulate large data frames

By the time the course finishes, students can use all of that new knowledge to create a simple game of rock, paper, scissors.

14. AI Programming with Python

This course should give students the skills needed to program for artificial intelligence using Python. It provides them with knowledge of Python in addition to various modules, such as Matplotlib, PyTorch, Pandas, and NumPy. It also features knowledge of the calculus and linear algebra needed to create a neural network.

This is an introductory course, and it can be a standalone for those who simply have an interest in AI programming and neural networks. Alternatively, it can be the first stepping stone on a path to a career in AI. The versatility of the course helps it appeal to both those who want a full-time role and those who are new to AI programming.

15. Learn to Code

This course does exactly as the title implies: Teaches students to code starting with the basics. It is an introduction to programming that students can follow up with deeper looks into AI, data science, machine learning, or app and web development.

During the course, students get an introduction to the top programming languages, including HTML, CSS, Python, and JavaScript. As such, this is a course for those who want to learn Python in addition to other programming languages. It should serve as a foundational course that participants can use to hone their skills before taking more advanced courses in Python and other programming languages.

16. Programming for Data Science with Python

This Python course will appeal to students interested in Python, specifically its applications for data science. The course provides students with the basic data programming tools that a developer needs, including git, SQL, and command line, as well as Python. Make sure to enroll in the Python track, as there is also an R track.

This course is appropriate for beginners with some basic ideas of programming. It includes introductions to Python programming, version control, and SQL, so there is no need for base knowledge in any of those areas to enroll.

17. Become a Computer Vision Expert

This program focuses on providing students with the skills to become a computer vision expert, which includes some Python knowledge. The main parts of the course include an introduction to computer vision, followed by advanced computer vision and some deep learning along with object localization and tracking.

Within the course, students will write programs that analyze images, recognize objects with deep learning models, and implement feature extraction. These computer vision applications all involve the use of Python. To write the applications, students will combine their Python knowledge with deep learning libraries and computer vision. Overall, the course teaches participants to analyze images using Python along with OpenCV before covering deeper learning. As such, enrollees should have some Python coding experience before taking the course.

18. Deep Learning

This deep learning course teaches how to build and then apply a deep neural network as a way to overcome challenges and take advantage of deep learning. It includes an introduction along with knowledge about neural networks, including recurrent and convolutional ones. It also covers generative adversarial networks and sentiment analysis models.

The various projects in this course use students’ Python knowledge as well as Python modules, such as Keras, NumPy, and TensorFlow PyTorch. Students will take their base knowledge of Python and apply it to deep learning, learning from experts and working professionals along the way.

19. Intro to Self-Driving Cars

Although this course is an introduction to self-driving cars, students will complete some of the programming in Python. Students will also be programming in C++ significantly during this course, so they should have an interest in both programming languages to take this course.

The course appeals to those with minimal programming experience, so students should not worry if they only have basic knowledge of Python and C++. Participants will learn the essentials to program a self-driving car, including probabilistic robotics, object-oriented programming, and machine learning.

20. Full Stack Web Developer

This course prepares students who want to become a full-stack web developer. Throughout the course, students will learn the skills needed to develop complex web applications on the server side, including applications that use databases for persistent data storage.

The course covers data modeling and SQL on the web, API documentation and development, server deployment, containerization, and identity access management. This course will prepare students for using Python programming language to create backend systems and use JavaScript, HTML, and CSS for front-end web development.

21. Predictive Analytics for Business

Taking this course will give students the skills to solve real-world problems in business via business intelligence and predictive analytics. The program requires prior coding experience. Students should have base Python and SQL knowledge, as the course will take them deeper into analytics and data with these skills.

Students will use that Python and SQL knowledge to learn about:

  • Data wrangling
  • A/B testing
  • Classification models
  • Time series forecasting
  • Clustering and segmentation
  • Using advanced analytics to solve problems

22. Become a Data Engineer

With this course, students will develop foundational knowledge for data engineering, which they can then use to become involved in big data. Topics include data modeling, data lakes, Spark, cloud data warehouses, data pipelines and airflow, and a capstone project.

This course appeals to those who already have a solid base knowledge of programming in Python and other languages. Students should be proficient in SQL as well as Python. This includes the ability to work with libraries, use classes, and write loops and functions in Python. In SQL, students should be comfortable with subqueries, aggregations, and joins.

23. Become a Data Analyst

This course provides an introduction to data analytics, using statistics, Python, and SQL. The course helps students create data-driven solutions and communicate critical findings. It covers:

  • Practical statistics
  • Introduction to data analysis
  • Data visualization using Python
  • Data wrangling

By the end of the course, participants will have developed a profile showing their skills in statistics and Python, including solving complex data problems. It provides the skills to become a data analyst in a company or as a freelancer.

24. Computer Programming for Beginners Learn Python Programming

This course teaches participants the basics of programming, making it easier to learn additional programming languages in the future. The course focuses on Python 3, providing students with a solid foundation of the programming language. It also teaches students the basic control structures and logic that are common among programming languages. The skills from the course are designed to make it simpler to learn additional programming languages or to deepen knowledge of Python in the future.

25. Python eCommerce | Build a Django eCommerce Web Application

This course gives students an overview of using Django, the popular library in Python. It uses Django version 1.11. From there, it builds on existing Python knowledge to help students create other aspects of an e-commerce web application. This includes integrating payments with Stripe, using Mailchimp to integrate email marketing, and using Heroku as a host to go live. The course also covers custom domains, implementing HTTPs, Bootstrap Version 4, REST APIs, jQuery Fast Track, and more. Students will build an internal search engine, use Django signals, and integrate email for notifications.

26. Free Marketing Automation Tutorial – Business Intelligence Development using Python 3

This is a free course that will help students build and automate a pipeline for marketing data as well as user behavior. Students will use Python libraries to develop the data automation process. Participants will then be able to conduct powerful analyses. The course also helps participants understand concepts like data automation, data engineer, marketing analytics, and data pipelines.

The course helps participants hone their skills for future job applications or to give them knowledge that they can apply to their own business. Before the course, enrollees should have a basic computer programming language knowledge along with some marketing experience.

27. DNA Research using Biopython

This course starts by teaching students about DNA (deoxyribonucleic acid) and how to work with it, using Python code and medical research to get a solution. Students will use Biopython along with its libraries to assist with research. The course should enhance existing object-oriented programming language skills, letting participants quickly fly through the Python coding.

The course will have specific research goals to help guide the use of Biopython on this introduction to the program. This should help students gain skills to use Biopython for future DNA research and serve as an introduction to bioinformatics.

28. Practical Data Analysis and Visualization with Python

With this course, students will learn how to solve daily problems using data science, data analytics, visualization, and machine learning models. Participants do not need to have any statistics or math knowledge to take the course, as enrollees will learn logic behind problems via intuition. After this course, participants can use Python to:

  • Build forecasting models featuring machine learning
  • Analyze bank statements
  • Analyze customer satisfaction
  • Develop classification models
  • Create and use logistic regression models
  • Classify images
  • Use NumPy, Pandas, and Scikit-learn
  • And more

29. Data Acquisition and Manipulation with Python

This course provides students with knowledge of Python data analysis tools, making it possible to acquire then analyze data in various formats. Students will connect with databases to add information to them, manipulate strings with Python, merge and combine data sets with Python, aggregate data, use BeautifulSoup, use Selenium to extract information from websites with Python, and program and use a Scrapy spider for web scraping.

Essentially, the course shows participants how to not only gather data in a clean format with Python but also transform it to make the data easier to use.

30. Python Design Patterns

This course teaches students how to design patterns as a way to reuse code, improve speed, and boost performance of Python applications. Enrollees will gain knowledge of which patterns programmers should use in development and at what point to use them. Students will use Builder, Factory, and other creational patterns. The course will show students how to encapsulate object behavior before delegating requests to it and to find simple methods of finding relationships between entities. The course features a downloadable resource and 2.5 hours of on-demand video.

31. Learn Python from Scratch with Real Applications

This course appeals to those who are complete beginners to Python and want to learn to code right from the start. The course covers the fundamentals of Python before delving into more advanced topics, such as using databases, Python functions, creating applications that use databases, and the PyQt5 graphic library. From there, students learn to use Python and PyQt5 to make great apps, including commercial desktop ones. Throughout the course, students will gain experience by building multiple apps, including database apps.

32. Learning Path: Python: Predictive Analysis with Python

This course will teach participants how to use Python libraries, like Scikit-learn and Pandas, to manipulate, visualize, and analyze data. Enrollees will read various data types with Pandas into dataframes to allow for data analysis and use Pandas to analyze and visualize various data types for real-world insights. The course also covers advanced techniques for Pandas, modeling time-series data and working with quantitative financial data.

Students should have basic Python knowledge before taking this course. It starts at the absolute beginning in terms of Pandas knowledge, so there is no need for any experience in that area.

33. Master Python Regular Expressions

This course starts at the beginning, teaching pupils about and how to use Python regular expressions. To ensure students get a firm handle on the concept, it includes a project as well as four case studies showing the potential uses of the new skills.

At the end of the course, students will be able to understand regular expressions and related concepts clearly. Students will also be able to write regular expressions for matching URLs, dates, and numbers. The course culminates in building a simple application to check passwords.

34. Getting Started with Python Bitcoin Programming

After this course, participants will be able to use Python programming skills to build Bitcoin trading bots, build software for mining Bitcoin, and write scripts to process payments in Bitcoin via an app or website. This is all possible by mastering the Python Bitcoin APIs. Students will use Python code to create wallets, addresses, and keys. Enrollees will also write software that analyzes Bitcoin transactions, creating graphs and reports.

The course features clear instructions as well as plenty of practical examples to illustrate the various concepts and skills learned.

35. Free Python Tutorial – Python Core and Advanced

This is a free course designed to help students master all of the features of Python. It features some introduction but can appeal to those with basic Python knowledge or those with almost none. Participants will execute a Python program and use Python Virtual Machine as well as the Eclipse IDE (PyDev). Participants will also:

  • Learn simple and collection types
  • Use various operators
  • Use Command line arguments
  • Define logic with looping constructs and conditional statements
  • Use generators, functions, and Lambda decorators
  • Implement encapsulation, inheritance, polymorphism, and abstraction
  • Handle exceptions
  • Do pattern matching with regular expressions
  • Use APIs to read as well as write files

36. The Complete Machine Learning Course with Python

In this course, students will create a profile that includes 12 different machine learning projects. Participants will learn and put to use skills related to Python, unsupervised machine learning, Scikit-Learn, Matplotlib, Seaborn, regression, and SVM. This is an updated version of a previously available course.

Enrollees will learn the most valuable machine learning tools to solve real-world problems. students will also fully understand ml algorithms performance metrics, including MSE, confusion matrix, recall, prevision, and R-squared, as well as classification and regression. This course gives participants the skills to join the in-demand machine learning field.

37. The Ultimate Python Masterclass – learn from scratch

This course takes participants from a beginner to a master of Python. At the end, students will have the skills needed to be a professional Python programmer. The course begins with the fundamentals of Python before guiding enrollees to create programs that use the full range of these fundamental concepts.

Throughout the course, students will gain experience and confidence in programming with Python and build up a portfolio that shows off these skills. Participants will develop the mindset of an app developer and begin to implement intermediate to advanced Python concepts.

38. Learning Path: Python: Design and Architect Python Apps

Following this course, students will be able to create high-performance applications using Python thanks to new knowledge of software architectural principals. The course begins by exploring Python in the world of application architecture. Participants will learn various architectural quality attributes as well as how to identify and correct design issues. The course also covers white box testing principles, multithreading, concurrency, prototype patterns, and design pattern categories.

Keep in mind that this course does require prior Python knowledge and experience. The course will appeal to those who want to design enterprise-grade applications as architects.

39. Start to Finish Unity Games and Python Coding

This course includes a section on Python coding and also teaches students to code in C# to make games in Unity. Participants will learn the basics of game design via coding in C# and program in Python. In the process, students will create a blackjack game and use loops, sets, dictionaries, and lists in Python.

Anyone interested in developing the skills to build games will appreciate the course. It includes plenty of introductory material, making it an appealing option for beginners. It also includes six bonus webinars for free and 58.5 hours of on-demand video.

40. Learn Python and Django from scratch: Create useful projects

This course is for complete beginners, so there is no need for any prior experience. The course will teach students the skills to create a development environment for Python and Django. Participants will:

  • Use Python editor
  • Create calculator, digital clock, and Django projects
  • Create a model in Django
  • Run migrations in Django
  • Query a database in Django
  • Administer a Django app

41. Python – Learn how to read write copy move search Excel files

Taking this course will give students the Python skills necessary to automate the use of Excel using Openpyxl. This ability will save participants a great deal of time via automation to read, write, and manipulate Excel files. Students will create, copy, and delete folders as well as copy, paste, cut, and delete Excel files. Enrollees will also be able to search flagged data in files and use that data to take action. Before taking this course, students should have some basic Python knowledge, including for loops, lists, and print statements.

42. Projects in Python for Intermediate: Build Python Projects

If students already have intermediate knowledge of Python, then this course will show how to further advance those skills by building complex projects. Participants will gain new skills and experience via various projects, including full-stack database-oriented apps. At the same time, completing the course will help build a portfolio since students will complete the projects. This should help with finding a job in Python developing more easily.

43. Python Flask for Beginners

Taking this course will give students the skills needed to create web applications in Python Flask. Participants will use Jinaj2 templates. Enrollees will also use other programming skills, including CSS to style the web app in Flask and HTML forms with the application. In the course, students will write a basic Flask application early on to help start practicing.

Although this course is for beginners to Flask, enrollees should have basic understanding of Python and know the basics of HTML.

44. MongoDB Tutorial – MongoDB and Python: Quick start

This course builds on existing basic knowledge of Python, teaching students MongoDB with Python as well as mongoengine. The course is free and short, showing participants skills by guiding them through the creation of an application like AirBnB with MongoDB and Python. Through the process, participants will gain the most useful MongoDB skills as well as valuable experience.

45. Code with Python (The Modern Python 3 Bootcamp)

This course appeals to complete beginners and teaches the skills needed to code with Python via almost 200 quizzes and exercise. Access to so many quizzes and exercises helps this course stand out since practice is the best way to hone Python skills. Students will gain full understanding of object-oriented programming, test-driven development, and testing. Enrollees will build games and large projects that include multiple files.

46. Python Programming Fundamentals

This is another appealing course for students who are complete beginners looking to learn Python. Participants will learn basic and complex Python topics, including decoders, loops, functions, and object-oriented programming. Students will also get practice by creating basic software and games. In addition to the video, there is a PDF download with practical study materials to build experience.

47. Free Python Tutorial – Python Hand-on Solve 200 Problems

This free course gives enrollees the chance to practice programming in Python via 200 problems. The number of problems covers a full range of applications and skill levels, appealing to anyone who wants extra practice. Beginners will appreciate the problems that focus on fundamentals, while experienced Python programmers will appreciate those related to data analysis and more.

48. Python Graphics Programming and Game Development

With this course, students will use their Python skills in a visual manner, learning to use Python to build various digital art tools. Enrollees can then use those tools to build basic programs to create graphics. Participants will also gain experience with programming video games and creating digital art. The course uses the Turtle Graphics library and requires basic knowledge of a programming language, which can be Python.

49. Quantitative Finance & Algorithmic Trading in Python

This advanced course lets students put existing Python skills to use with algorithmic trading. Students will gain understanding of stock market fundamentals, Modern Portfolio Theory, CAPM, stochastic processes, Black-Scholes mode, Monte-Carlo simulations, and Value-at-Risk. Participants will then use previous Python skills and this new knowledge for algorithmic trading.

This course requires previous Python knowledge. Pupils should also have an interest in math and statistics, as the course will be filled with those subjects. At the end of the course, students will have learned the financial engineering basics.

50. Hands-On Python & Xcode Image Processing: Building Games & Apps

Students do not need any prior Python experience to take this course since it begins with basics of programming in Python, including dictionaries, sets, loops, and lists. Participants will create classes, import with Python, handle errors, and make a blackjack game.

The course will also teach advanced image-related skills in Python, such as using Swift’s facial recognition software; detecting text in images; applying filters; superimposing images; letting users pan and zoom; and creating an interface so enrollees can load, save, and modify images.